TY - GEN
T1 - On the scalability of particle swarm optimisation
AU - Piccand, Sébastien
AU - O'Neill, Michael
AU - Walker, Jacqueline
PY - 2008
Y1 - 2008
N2 - Particle swarm has proven to be competitive to other evolutionary algorithms in the field of optimization, and in many cases enables a faster convergence to the ideal solution. However, like any optimization algorithm it seems to have difficulties handling optimization problems of high dimension. Here we first show that dimensionality is really a problem for the classical particle swarm algorithms. We then show that increasing the swarm size can be necessary to handle problem of high dimensions but is not enough. We also show that the issue of scalability occurs more quickly on some functions.
AB - Particle swarm has proven to be competitive to other evolutionary algorithms in the field of optimization, and in many cases enables a faster convergence to the ideal solution. However, like any optimization algorithm it seems to have difficulties handling optimization problems of high dimension. Here we first show that dimensionality is really a problem for the classical particle swarm algorithms. We then show that increasing the swarm size can be necessary to handle problem of high dimensions but is not enough. We also show that the issue of scalability occurs more quickly on some functions.
UR - http://www.scopus.com/inward/record.url?scp=55749100114&partnerID=8YFLogxK
U2 - 10.1109/CEC.2008.4631134
DO - 10.1109/CEC.2008.4631134
M3 - Conference contribution
AN - SCOPUS:55749100114
SN - 9781424418237
T3 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
SP - 2505
EP - 2512
BT - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
T2 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
Y2 - 1 June 2008 through 6 June 2008
ER -